[1] H.S. Ulusoy, M.Q. Feng, P.J. Fanning, System identification of a building from multiple seismic records, Earthquake Engineering & Structural Dynamics, 40(6) (2011) 661-674.
[2] M. Inel, H.B. Ozmen, B.T. Cayci, Determination of period of RC buildings by the ambient vibration method, Advances in Civil Engineering, 2019 (2019) 1-10.
[3] M. Mirtaheri, F. Salehi, Ambient vibration testing of existing buildings: Experimental, numerical and code provisions, Advances in Mechanical Engineering, 10(4) (2018) 1687814018772718.
[4] O.C. Celik, H.P. Gülkan, Processing forced vibration test records of structural systems using the analytic signal, Journal of Vibration and Control, 27(19-20) (2021) 2253-2267.
[5] P. Van Overschee, B. De Moor, N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems, Automatica, 30(1) (1994) 75-93.
[6] E.P. Reynders, Uncertainty quantification in data-driven stochastic subspace identification, Mechanical Systems and Signal Processing, 151 (2021) 107338.
[7] E. Reynders, System identification methods for (operational) modal analysis: review and comparison, Archives of Computational Methods in Engineering, 19 (2012) 51-124.
[8] J.M. Brownjohn, Ambient vibration studies for system identification of tall buildings, Earthquake engineering & structural dynamics, 32(1) (2003) 71-95.
[9] B. Moaveni, X. He, J.P. Conte, J.I. Restrepo, M. Panagiotou, System identification study of a 7-story full-scale building slice tested on the UCSD-NEES shake table, Journal of Structural Engineering, 137(6) (2011) 705-717.
[10] E. Tronci, M. De Angelis, R. Betti, V. Altomare, Multi-stage semi-automated methodology for modal parameters estimation adopting parametric system identification algorithms, Mechanical Systems and Signal Processing, 165 (2022) 108317.
[11] M. Pourgholi, R. Tarinejad, M.E. Khabir, M. Mohammadzadeh Gilarlue, System identification of Karun IV Dam using balanced stochastic subspace algorithm considering the uncertainty of results, Journal of Vibration and Control, (2022) 10775463221133591.
[12] C. Priori, M. De Angelis, R. Betti, On the selection of user-defined parameters in data-driven stochastic subspace identification, Mechanical Systems and Signal Processing, 100 (2018) 501-523.
[13] S. Li, J.-T. Wang, A.-Y. Jin, G.-H. Luo, Parametric analysis of SSI algorithm in modal identification of high arch dams, Soil Dynamics and Earthquake Engineering, 129 (2020) 105929.
[14] T. Katayama, Subspace-Based System Identification-A View from Realization Theory, Systems, Control and Information Engineers, 41 (1997) 380-387.
[15] E.J. Hannan, M. Deistler, The statistical theory of linear systems, SIAM, 2012.
[16] T. Katayama, H. Kawauchi, G. Picci, Subspace identification of closed loop systems by stochastic realization, in: CD-ROM Preprints 15th IFAC World Congress, Barcelona, 2002.
[17] M. Verhaegen, P. Dewilde, Subspace model identification part 2. Analysis of the elementary output-error state-space model identification algorithm, International journal of control, 56(5) (1992) 1211-1241.
[18] E. Reynders, G. De Roeck, Reference-based combined deterministic–stochastic subspace identification for experimental and operational modal analysis, Mechanical Systems and Signal Processing, 22(3) (2008) 617-637.
[19] P. Van Overschee, B.L. De Moor, Subspace identification for linear systems: theory, implementation, applications, Kluwer academic publishers Dordrecht, 1996.
[20] A. Deraemaeker, E. Reynders, G. De Roeck, J. Kullaa, Vibration-based structural health monitoring using output-only measurements under changing environment, Mechanical systems and signal processing, 22(1) (2008) 34-56.
[21] F. Magalhaes, A. Cunha, E. Caetano, Online automatic identification of the modal parameters of a long span arch bridge, Mechanical Systems and Signal Processing, 23(2) (2009) 316-329.
[22] S. Kim, M. Vanderploeg, QR decomposition for state space representation of constrained mechanical dynamic systems, (1986).
[23] H. Tanaka, T. Katayama, A stochastic realization in a Hilbert space based on “LQ decomposition” with application to subspace identification, in: 13th IFAC Symposium on System Identification (SYSID 2003), 2003, pp. 899-904.
[24] J.C. Santamarina, D. Fratta, Discrete signals and inverse problems, An Introduction for Engineers and Scientists. UK: Wiley & Sons, (2005).
[25] J.-H. Yi, C.-B. Yun, Comparative study on modal identification methods using output-only information, Structural Engineering and Mechanics, 17(3-4) (2004) 445-466.
[26] M. Verhaegen, V. Verdult, Filtering and system identification: a least squares approach, Cambridge university press, United Kingdom, Cambridge, 2007.
[27] C. Rainieri, G. Fabbrocino, Influence of model order and number of block rows on accuracy and precision of modal parameter estimates in stochastic subspace identification, International Journal of Lifecycle Performance Engineering 10, 1(4) (2014) 317-334.
[28] E. Reynders, J. Houbrechts, G. De Roeck, Fully automated (operational) modal analysis, Mechanical Systems and Signal Processing, 29 (2012) 228-250.
[29] M. Ester, H.-P. Kriegel, J. Sander, X. Xu, A density-based algorithm for discovering clusters in large spatial databases with noise, in: kdd, Munchen, Germany, 1996, pp. 226-231.
[30] P. Andersen, Identification of civil engineering structures using vector ARMA models, Aalborg University, Aalborg, Denmark, 1997.
[31] R. Tarinejad, M. Pourgholi, Processing of Ambient Vibration Results using Stochastic Subspace Identification based on Canonical Correlation Analysis, Modares Mechanical Engineering, 15(7) (2015).
[32] M. Damadi pour, R. Tarinejad, System identification of a concrete arch dam and calibration of its finite element model with emphasis on nonuniform ground motion, Tabriz, Tabriz, 2012.